This notebook contains a set of analyses for analyzing schlagdawg’s boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that the specified user is likely to own. This enables us to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?
We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.
What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.
We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.
We’ll examine predictive models trained on a user’s collection for games published through 2020. How many games has the user owned/rated/played in the training set (games prior to 2020)?
username | dataset | period | games_owned | games_rated |
schlagdawg | training | published before 2020 | 74 | 0 |
schlagdawg | validation | published 2020 | 11 | 0 |
schlagdawg | test | published after 2020 | 13 | 0 |
The main outcome we will be modeling for the user is owned, which refers to whether the user currently owns or has a previously owned a game in their collection. Our goal is to train a predictive model to learn the probability that a user will add a game to their collection based on its observable features. This amounts to looking at historical data and looking to find patterns that exist between features of games and games present in the user’s collection.
One of the models we trained was a decision tree, which looks for decision rules that can be used to separate games the user owns from games they don’t. The resulting model produces a decision corresponding to yes or no statements: to explain why the model predicts the user to own game, we start at the top of the tree and follow the rules that were learned from the training data.
Note: the tree below has been further pruned to make it easier to visualize.
Decision trees are highly interpretible models that are easy to train and can identify important interactions and nonlinearities present in the data. Individual trees have the drawback of being less predictive than other common models, but it can be useful to look at them to gain some understanding of key predictors and relationships found in the training data.
We can examine coefficients from another model we trained, which is a logistic regression with elastic net regularization (which I will refer to as a penalized logistic regression). Positive values indicate that a feature increases a user’s probability of owning/rating a game, while negative values indicate a feature decreases the probability. To be precise, the coefficients indicate the effect of a particular feature on the log-odds of a user owning a game.
Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.
Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.
% of Games with Feature | ||||
username | Feature | User_Collection | All_Games | Ratio |
schlagdawg | Race | 8.1% | 1.0% | 8.24 |
schlagdawg | Pegasus Spiele | 16.2% | 2.2% | 7.44 |
schlagdawg | Rio Grande Games | 12.2% | 1.9% | 6.38 |
schlagdawg | Map Continental National Scale | 10.8% | 1.9% | 5.58 |
schlagdawg | Take That | 18.9% | 5.1% | 3.71 |
schlagdawg | Solitaire Only Games | 5.4% | 1.5% | 3.70 |
schlagdawg | Word Game | 8.1% | 2.2% | 3.61 |
schlagdawg | Kosmos | 6.8% | 2.0% | 3.42 |
schlagdawg | Cooperative Game | 18.9% | 6.2% | 3.05 |
schlagdawg | Deduction Game | 13.5% | 5.1% | 2.65 |
schlagdawg | Crowdfunding Kickstarter | 29.7% | 12.5% | 2.37 |
schlagdawg | Card Game | 48.6% | 29.4% | 1.65 |
schlagdawg | Party Game | 13.5% | 9.3% | 1.45 |
schlagdawg | Two Player Only Games | 14.9% | 17.4% | 0.85 |
schlagdawg | Dice Rolling | 10.8% | 28.4% | 0.38 |
schlagdawg | Storytelling | 0.0% | 2.1% | 0.00 |
Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.
Displaying the 100 games from the training set with the highest probability of ownership, highlighting in blue games the user has owned.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 2008 | 38453 | Space Alert | 0.890 | no |
2 | 2016 | 167791 | Terraforming Mars | 0.748 | no |
3 | 2018 | 255692 | New Frontiers | 0.670 | no |
4 | 2018 | 199792 | Everdell | 0.647 | no |
5 | 2005 | 18258 | Mission: Red Planet | 0.601 | no |
6 | 2016 | 205158 | Codenames: Deep Undercover | 0.565 | no |
7 | 2017 | 162886 | Spirit Island | 0.524 | yes |
8 | 2016 | 191189 | Aeon's End | 0.476 | no |
9 | 2016 | 169786 | Scythe | 0.448 | no |
10 | 2007 | 28143 | Race for the Galaxy | 0.431 | yes |
11 | 2014 | 157354 | Five Tribes | 0.423 | no |
12 | 2018 | 313010 | Cosmic Encounter: 42nd Anniversary Edition | 0.422 | no |
13 | 2014 | 150926 | Roll Through the Ages: The Iron Age | 0.400 | no |
14 | 2003 | 7717 | Carcassonne: The Castle | 0.395 | no |
15 | 2017 | 220775 | Codenames: Disney – Family Edition | 0.389 | no |
16 | 2004 | 9609 | War of the Ring | 0.351 | no |
17 | 2003 | 6068 | Queen's Necklace | 0.341 | no |
18 | 2012 | 124742 | Android: Netrunner | 0.332 | no |
19 | 2016 | 205398 | Citadels | 0.321 | no |
20 | 2018 | 256916 | Concordia Venus | 0.289 | no |
21 | 2018 | 259829 | Loser | 0.289 | no |
22 | 2006 | 25613 | Through the Ages: A Story of Civilization | 0.281 | no |
23 | 1995 | 93 | El Grande | 0.279 | no |
24 | 2014 | 158882 | Elevenses for One | 0.273 | no |
25 | 2011 | 96848 | Mage Knight Board Game | 0.269 | no |
26 | 2012 | 119506 | Freedom: The Underground Railroad | 0.263 | no |
27 | 2018 | 222509 | Lords of Hellas | 0.225 | no |
28 | 2015 | 177639 | Raptor | 0.219 | yes |
29 | 2019 | 270971 | Era: Medieval Age | 0.218 | no |
30 | 2002 | 4396 | Odin's Ravens | 0.204 | no |
31 | 2017 | 205597 | Jump Drive | 0.189 | no |
32 | 2014 | 132531 | Roll for the Galaxy | 0.186 | no |
33 | 2019 | 217576 | Hellenica: Story of Greece | 0.185 | no |
34 | 2017 | 200847 | Secrets | 0.185 | no |
35 | 2019 | 228328 | Rurik: Dawn of Kiev | 0.183 | no |
36 | 2018 | 244711 | Newton | 0.182 | no |
37 | 2018 | 247763 | Underwater Cities | 0.182 | no |
38 | 2013 | 143693 | Glass Road | 0.181 | no |
39 | 2017 | 233078 | Twilight Imperium: Fourth Edition | 0.178 | no |
40 | 2018 | 233080 | Book of Dragons | 0.163 | no |
41 | 2012 | 129622 | Love Letter | 0.163 | yes |
42 | 2019 | 253574 | Crusader Kings | 0.161 | no |
43 | 2019 | 283849 | The Only Word: the Party Word Game | 0.161 | no |
44 | 2013 | 144239 | Impulse | 0.156 | no |
45 | 2017 | 227789 | Heaven & Ale | 0.155 | no |
46 | 2016 | 149787 | Perdition's Mouth: Abyssal Rift | 0.150 | no |
47 | 2018 | 236457 | Architects of the West Kingdom | 0.150 | no |
48 | 2019 | 265285 | Queenz: To Bee or Not to Bee | 0.137 | no |
49 | 2004 | 9202 | Saga | 0.137 | no |
50 | 2019 | 284818 | Caylus 1303 | 0.136 | no |
51 | 2015 | 155708 | Tiny Epic Defenders | 0.136 | no |
52 | 2019 | 281946 | Aftermath | 0.136 | no |
53 | 2007 | 28720 | Brass: Lancashire | 0.135 | no |
54 | 2019 | 276025 | Maracaibo | 0.135 | no |
55 | 2015 | 182047 | Austerity | 0.130 | no |
56 | 2018 | 249821 | Codenames: Harry Potter | 0.130 | no |
57 | 2019 | 241724 | Villagers | 0.128 | no |
58 | 2017 | 179172 | Unfair | 0.128 | no |
59 | 2014 | 147020 | Star Realms | 0.125 | no |
60 | 2012 | 122515 | Keyflower | 0.124 | no |
61 | 1996 | 932 | Top Race | 0.123 | no |
62 | 2016 | 203715 | The Shooting Party | 0.120 | no |
63 | 2019 | 266936 | Slyville | 0.118 | no |
64 | 1999 | 50 | Lost Cities | 0.118 | yes |
65 | 2017 | 174430 | Gloomhaven | 0.117 | no |
66 | 2016 | 156858 | Black Orchestra | 0.114 | no |
67 | 1997 | 42 | Tigris & Euphrates | 0.113 | no |
68 | 2010 | 73439 | Troyes | 0.113 | no |
69 | 2016 | 205637 | Arkham Horror: The Card Game | 0.111 | no |
70 | 2013 | 124361 | Concordia | 0.111 | yes |
71 | 2011 | 103649 | The City | 0.109 | no |
72 | 2014 | 154203 | Imperial Settlers | 0.108 | no |
73 | 2009 | 54998 | Cyclades | 0.107 | no |
74 | 2016 | 199766 | Listography: The Game | 0.105 | no |
75 | 2018 | 205896 | Rising Sun | 0.105 | no |
76 | 2019 | 265736 | Tiny Towns | 0.104 | yes |
77 | 2017 | 234671 | Pandemic: Rising Tide | 0.104 | no |
78 | 2012 | 121921 | Robinson Crusoe: Adventures on the Cursed Island | 0.104 | no |
79 | 2018 | 260428 | Pandemic: Fall of Rome | 0.101 | no |
80 | 2011 | 79828 | A Few Acres of Snow | 0.101 | no |
81 | 2004 | 9440 | Maharaja: The Game of Palace Building in India | 0.101 | no |
82 | 2008 | 40381 | Modern Art Card Game | 0.100 | no |
83 | 2004 | 9209 | Ticket to Ride | 0.099 | no |
84 | 2019 | 283863 | The Magnificent | 0.099 | no |
85 | 2018 | 227545 | Spy Club | 0.099 | no |
86 | 2019 | 230244 | Black Angel | 0.099 | no |
87 | 2018 | 245638 | Coimbra | 0.095 | no |
88 | 2018 | 218421 | Street Masters | 0.095 | no |
89 | 2011 | 103686 | Mundus Novus | 0.094 | no |
90 | 2012 | 87821 | Kingdom of Solomon | 0.094 | no |
91 | 2019 | 256876 | Football Highlights 2052 | 0.093 | no |
92 | 2009 | 55911 | Albion | 0.093 | no |
93 | 2014 | 155987 | Abyss | 0.091 | no |
94 | 1999 | 304 | Evergreen | 0.091 | no |
95 | 2015 | 172385 | Porta Nigra | 0.091 | no |
96 | 2009 | 58798 | Cardcassonne | 0.090 | no |
97 | 2016 | 177590 | 13 Days: The Cuban Missile Crisis | 0.089 | no |
98 | 2015 | 178900 | Codenames | 0.089 | yes |
99 | 2016 | 207336 | Honshū | 0.088 | no |
100 | 2010 | 55601 | Sneaks & Snitches | 0.086 | no |
This section contains a variety of visualizations and metrics for assessing the performance of the model(s) during resampling. If you’re not particularly interested in predictive modeling, skip down further to the predictions from the model.
An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).
We can more formally assess how well each model did in resampling by looking at the area under the receiver operating characteristic curve. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.
wflow_id | .metric | .estimator | .estimate |
GLM | roc_auc | binary | 0.89 |
Decision Tree | roc_auc | binary | 0.71 |
Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing. A gains chart is another way to view this.
While we are probably more interested in the lift provided by the models to evaluate their efficacy, we can also explore the optimal cutpoint if we wanted to define a hard threshold for identifying games a user will own vs not own.
The threshold we select depends on how we much we care about false positives (games the model predicts that the user does not own) vs false negatives (games the user owns that the model does not predict). We can toggle threshold to
Finally, we can understand the performance of the model by examining its calibration. If the model assigns a probability of 5%, how often does the outcome actually occur? A well calibrated model is one in which the predicted probabilities reflect the probabilities we would observe in the actual data. We can assess the calibration of a model by grouping its predictions into bins and assessing how often we observe the outcome versus how often our model expects to observe the outcome.
A model that is well calibrated will closely follow the dashed line - its expected probabilities match that of the observed probabilities. A model that consistently underestimates the probability of the event will be over this dashed line, be a while a model that overestimates the probability will be under the dashed line.
What games does the model think schlagdawg is most likely to own that are not in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2008 | 38453 | Space Alert | 0.890 | no |
2016 | 167791 | Terraforming Mars | 0.748 | no |
2018 | 255692 | New Frontiers | 0.670 | no |
2018 | 199792 | Everdell | 0.647 | no |
2005 | 18258 | Mission: Red Planet | 0.601 | no |
What games does the model think schlagdawg is least likely to own that are in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2010 | 315048 | Survive: Escape from Atlantis! | 0.000 | yes |
2019 | 142379 | Escape Plan | 0.001 | yes |
2018 | 250458 | Gùgōng | 0.001 | yes |
1998 | 153 | Take 5! | 0.001 | yes |
2018 | 297234 | Taskmaster: The Board Game | 0.001 | yes |
Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned.
rank | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
1 | Android: Netrunner | Glass Road | Five Tribes | Raptor | Terraforming Mars | Spirit Island | New Frontiers | Era: Medieval Age |
2 | Freedom: The Underground Railroad | Impulse | Roll Through the Ages: The Iron Age | Tiny Epic Defenders | Codenames: Deep Undercover | Codenames: Disney – Family Edition | Everdell | Hellenica: Story of Greece |
3 | Love Letter | Concordia | Elevenses for One | Austerity | Aeon's End | Jump Drive | Cosmic Encounter: 42nd Anniversary Edition | Rurik: Dawn of Kiev |
4 | Keyflower | Gravwell: Escape from the 9th Dimension | Roll for the Galaxy | Porta Nigra | Scythe | Secrets | Concordia Venus | Crusader Kings |
5 | Robinson Crusoe: Adventures on the Cursed Island | Coal Baron | Star Realms | Codenames | Citadels | Twilight Imperium: Fourth Edition | Loser | The Only Word: the Party Word Game |
6 | Kingdom of Solomon | Lewis & Clark: The Expedition | Imperial Settlers | Smash Up: Munchkin | Perdition's Mouth: Abyssal Rift | Heaven & Ale | Lords of Hellas | Queenz: To Bee or Not to Bee |
7 | Polis: Fight for the Hegemony | Train Heist | Abyss | Love Letter: The Hobbit – The Battle of the Five Armies | The Shooting Party | Unfair | Newton | Caylus 1303 |
8 | Descent: Journeys in the Dark (Second Edition) | SOS Titanic | Eminent Domain: Microcosm | Coffee Roaster | Black Orchestra | Gloomhaven | Underwater Cities | Aftermath |
9 | Qin | Rococo | Evolution | 504 | Arkham Horror: The Card Game | Pandemic: Rising Tide | Book of Dragons | Maracaibo |
10 | Barbarian Vince | Colonialism | Paperback | Brick Party | Listography: The Game | Black Sonata | Architects of the West Kingdom | Villagers |
11 | Shadows over Camelot: The Card Game | Bomb Squad | Roll Through the Ages: The Iron Age with Mediterranean Expansion | DRCongo | 13 Days: The Cuban Missile Crisis | Exploding Kittens: Newbie Edition | Codenames: Harry Potter | Slyville |
12 | Starship Merchants | Antidote | Supermarché | Murderer's Row | Honshū | Queendomino | Rising Sun | Tiny Towns |
13 | Antike Duellum | Anomia: Party Edition | Cheesonomics | Lost Legacy: Second Chronicle – Vorpal Sword & Whitegold Spire | Junta: Las Cartas | Banned Words | Pandemic: Fall of Rome | The Magnificent |
14 | (Your Name Here) and the Argonauts | Legacy: The Testament of Duke de Crecy | Linko! | Mission: Red Planet (Second Edition) | Coal Baron: The Great Card Game | Magic Maze | Spy Club | Black Angel |
15 | The Palaces of Carrara | Nauticus | Onirim (Second Edition) | Bullfrogs | Pentaquark | Codenames: Duet | Coimbra | Football Highlights 2052 |
16 | Ascension: Immortal Heroes | The Little Prince: Make Me a Planet | Splendor | Letter Tycoon | Flamme Rouge | The Quest for El Dorado | Street Masters | Quodd Heroes |
17 | Wiz-War (Eighth Edition) | Outer Earth | Shipwrights of the North Sea | RallyRas | Star Trek: Frontiers | LYNGK | Card Capture | Paladins of the West Kingdom |
18 | Ginkgopolis | Mascarade | AquaSphere | Sylvion | Smash Up: Cease and Desist | Ex Libris | Hokkaido | Western Empires |
19 | [_BLÄNK] | Empire Engine | Tiny Epic Kingdoms | Valley of the Kings: Afterlife | SiXeS | The Godfather: Corleone's Empire | Micropolis | Blitzkrieg!: World War Two in 20 Minutes |
20 | Merchant of Venus (Second Edition) | The Walking Dead Card Game | Black Fleet | Exploding Kittens: NSFW Deck | Pandemic: Iberia | Smash Up: What Were We Thinking? | Jurassic Park: Danger! | The Quest for El Dorado: The Golden Temples |
21 | Guildhall | Animals Frightening Night! | The Worst Game Ever | Salem 1692 | Munchkin Grimm Tidings | Gaia Project | Palm Island | Tiny Epic Mechs |
22 | Kemet | Tash-Kalar: Arena of Legends | Haru Ichiban | Dexikon | Assembly | Tesla vs. Edison: Duel | Sprawlopolis | Nights of Fire: Battle for Budapest |
23 | Pax Porfiriana | Prosperity | Land 6 | Tiny Epic Galaxies | Kingdomino | Tournament Fishing: The Deckbuilding Game | The Grizzled: Armistice Edition | Yukon Airways |
24 | Libertalia | Room 25 | Istanbul | I Hate Zombies | Snooker Solitaire | Outlive | Medieval | Aeon's End: Legacy |
25 | Uchronia | Pocket Imperium | Coup: Rebellion G54 | Baseball Highlights: 2045 | Inis | Word Domination | Hardback | A Rusty Throne |
This is an interactive table for the model’s predictions for the training set (from resampling).
We’ll validate the model by looking at its predictions for games published in 2020. That is, how well did a model trained on a user’s collection through 2020 perform in predicting games for the user in 2020?
username | outcome | dataset | method | .metric | .estimate |
schlagdawg | owned | validation | GLM | roc_auc | 0.707 |
schlagdawg | owned | validation | Decision Tree | roc_auc | 0.594 |
Table of top 50 games from 2020, highlighting games that the user owns.
Published | ID | Name | Pr(Owned) | Owned |
2020 | 184267 | On Mars | 0.708 | yes |
2020 | 311193 | Anno 1800 | 0.203 | no |
2020 | 296237 | Warp's Edge | 0.155 | no |
2020 | 291457 | Gloomhaven: Jaws of the Lion | 0.135 | no |
2020 | 309110 | Food Chain Island | 0.123 | yes |
2020 | 298572 | Cosmic Encounter Duel | 0.113 | no |
2020 | 292333 | Cowboys II: Cowboys & Indians Edition | 0.112 | no |
2020 | 279537 | The Search for Planet X | 0.087 | no |
2020 | 276205 | Philosophia: Dare to be Wise | 0.082 | no |
2020 | 306481 | Tawantinsuyu: The Inca Empire | 0.076 | no |
2020 | 298371 | Wild Space | 0.073 | no |
2020 | 282954 | Paris | 0.068 | no |
2020 | 269420 | Ragemore | 0.066 | no |
2020 | 282922 | Windward | 0.065 | no |
2020 | 316554 | Dune: Imperium | 0.064 | no |
2020 | 317847 | The Lost Words | 0.064 | no |
2020 | 295486 | My City | 0.060 | yes |
2020 | 256317 | Guild Master | 0.058 | no |
2020 | 316377 | 7 Wonders (Second Edition) | 0.058 | no |
2020 | 278042 | Crusader Kingdoms: The War for the Holy Land | 0.054 | no |
2020 | 308765 | Praga Caput Regni | 0.054 | no |
2020 | 296151 | Viscounts of the West Kingdom | 0.053 | no |
2020 | 306687 | Get Out of Colditz: The Card Game | 0.051 | no |
2020 | 306040 | Merv: The Heart of the Silk Road | 0.051 | no |
2020 | 301919 | Pandemic: Hot Zone – North America | 0.050 | no |
2020 | 300010 | Dragomino | 0.048 | no |
2020 | 316750 | The Princess Bride Adventure Book Game | 0.047 | no |
2020 | 319966 | The King Is Dead: Second Edition | 0.042 | yes |
2020 | 283155 | Calico | 0.041 | yes |
2020 | 308416 | Tapeworm | 0.038 | no |
2020 | 293296 | Splendor: Marvel | 0.037 | no |
2020 | 288169 | The Fox in the Forest Duet | 0.037 | no |
2020 | 233673 | Exploration | 0.036 | no |
2020 | 262274 | D6: Dungeons, Dudes, Dames, Danger, Dice and Dragons! | 0.036 | no |
2020 | 288513 | Tranquility | 0.034 | no |
2020 | 306735 | Under Falling Skies | 0.034 | no |
2020 | 294294 | Letterpress | 0.034 | no |
2020 | 320819 | Dinner in Paris | 0.033 | no |
2020 | 302734 | Master Word | 0.032 | no |
2020 | 299179 | Chancellorsville 1863 | 0.031 | no |
2020 | 282081 | The Zorro Dice Game | 0.031 | no |
2020 | 316412 | The LOOP | 0.031 | no |
2020 | 274037 | Solar Storm | 0.029 | no |
2020 | 272739 | Clinic: Deluxe Edition | 0.028 | no |
2020 | 318983 | Faiyum | 0.028 | no |
2020 | 298047 | Marvel United | 0.027 | no |
2020 | 293678 | Stellar | 0.027 | no |
2020 | 300753 | Cross Clues | 0.027 | no |
2020 | 303669 | Magic Rabbit | 0.026 | no |
2020 | 325038 | The Brambles: A Solo Card Game | 0.026 | no |
We can then refit our model to the training and validation set in order to predict all upcoming games for the user.
Examine the top 100 upcoming games, highlighting in blue ones the user already owns.
Published | ID | Name | Pr(Owned) | Owned |
2021 | 324242 | Sheepy Time | 0.513 | no |
2021 | 295947 | Cascadia | 0.475 | yes |
2021 | 339484 | Savannah Park | 0.214 | no |
2022 | 331106 | The Witcher: Old World | 0.206 | no |
2021 | 339789 | Welcome to the Moon | 0.205 | no |
2021 | 283387 | Rocketmen | 0.189 | no |
2021 | 313841 | Lunar Base | 0.183 | no |
2022 | 310873 | Carnegie | 0.171 | no |
2021 | 314088 | Agropolis | 0.158 | yes |
2023 | 347909 | Rogue Angels: Legacy of the Burning Suns | 0.148 | no |
2021 | 298102 | Roll Camera!: The Filmmaking Board Game | 0.142 | no |
2021 | 305761 | Whale Riders | 0.126 | no |
2021 | 322709 | Ugly Gryphon Inn | 0.111 | yes |
2021 | 260524 | Beyond Humanity: Colonies | 0.109 | no |
2021 | 304985 | Dark Ages: Holy Roman Empire | 0.105 | no |
2021 | 295535 | Dark Ages: Heritage of Charlemagne | 0.105 | no |
2022 | 349067 | The Lord of the Rings: The Card Game – Revised Core Set | 0.101 | no |
2021 | 303954 | Pax Viking | 0.100 | no |
2021 | 329873 | GROVE: A 9 card solitaire game | 0.100 | no |
2021 | 298069 | Cubitos | 0.097 | no |
2021 | 340909 | Gloomholdin' | 0.097 | no |
2022 | 347703 | First Rat | 0.093 | no |
2022 | 349793 | Age of Rome | 0.093 | no |
2021 | 332944 | Sobek: 2 Players | 0.092 | no |
2021 | 340041 | Kingdomino Origins | 0.091 | no |
2021 | 318996 | Welcome to Sysifus Corp | 0.084 | no |
2022 | 317511 | Tindaya | 0.079 | no |
2021 | 338980 | Eastern Empires | 0.077 | no |
2022 | 295770 | Frosthaven | 0.074 | no |
2021 | 319792 | Fly-A-Way | 0.070 | no |
2021 | 342246 | Feuding Foodies | 0.069 | no |
2021 | 301366 | Caves of Rwenzori | 0.066 | no |
2022 | 338468 | Paperback Adventures | 0.065 | no |
2021 | 313730 | Harsh Shadows | 0.064 | no |
2022 | 311988 | Frostpunk: The Board Game | 0.063 | no |
2021 | 342942 | Ark Nova | 0.062 | no |
2021 | 328479 | Living Forest | 0.057 | no |
2022 | 331401 | Dog Park | 0.052 | no |
2021 | 331328 | Unsurmountable | 0.051 | no |
2022 | 342900 | Earthborne Rangers | 0.051 | no |
2021 | 334782 | Bayou Bash | 0.049 | no |
2022 | 330950 | Age of Galaxy | 0.048 | no |
2021 | 291847 | Mantis Falls | 0.048 | no |
2022 | 299106 | Fractal: Beyond the Void | 0.046 | no |
2021 | 341169 | Great Western Trail (Second Edition) | 0.046 | no |
2021 | 256680 | Return to Dark Tower | 0.045 | no |
2021 | 306202 | Philosophia: Floating World | 0.044 | no |
2021 | 290236 | Canvas | 0.044 | no |
2021 | 304333 | Zoollywood | 0.044 | no |
2022 | 258779 | Planet Unknown | 0.043 | no |
2021 | 328286 | Mission ISS | 0.042 | no |
2021 | 249277 | Brazil: Imperial | 0.040 | no |
2021 | 298378 | Maharaja | 0.040 | no |
2021 | 342562 | ROVE: Results-Oriented Versatile Explorer | 0.039 | yes |
2021 | 314491 | Meadow | 0.039 | no |
2021 | 344415 | Trek 12: Amazonia | 0.039 | no |
2022 | 284842 | So, You've Been Eaten | 0.039 | no |
2021 | 343847 | Dustbiters | 0.038 | no |
2021 | 266448 | Imperium: The Contention | 0.038 | no |
2021 | 291859 | Riftforce | 0.036 | no |
2021 | 285967 | Ankh: Gods of Egypt | 0.036 | no |
2021 | 291572 | Oath: Chronicles of Empire and Exile | 0.035 | yes |
2021 | 265771 | Dance Card! | 0.035 | no |
2021 | 339906 | The Hunger | 0.034 | no |
2021 | 257706 | Zoo-ography | 0.034 | no |
2021 | 287608 | Epic Card Game: Duels | 0.033 | no |
2021 | 331787 | Tiny Epic Dungeons | 0.033 | no |
2021 | 337787 | Summer Camp | 0.032 | no |
2022 | 305096 | Endless Winter: Paleoamericans | 0.032 | no |
2021 | 340834 | Gravwell: 2nd Edition | 0.030 | no |
2021 | 322703 | Death Valley | 0.030 | no |
2021 | 253512 | Blabel | 0.030 | no |
2022 | 334065 | Verdant | 0.030 | no |
2021 | 295607 | Canopy | 0.029 | yes |
2021 | 299566 | Batman: The Animated Series Adventures – Shadow of the Bat | 0.029 | no |
2021 | 312594 | The Forest Watch | 0.029 | no |
2021 | 345976 | System Gateway (fan expansion for Android: Netrunner) | 0.029 | no |
2021 | 344405 | Cartaventura: Oklahoma | 0.029 | no |
2021 | 309319 | Apogee | 0.029 | no |
2021 | 329670 | Pandemic: Hot Zone – Europe | 0.029 | no |
2022 | 305462 | The Age of Atlantis | 0.028 | no |
2021 | 299255 | Vienna Connection | 0.027 | no |
2022 | 332393 | Bridge City Poker | 0.027 | no |
2022 | 284118 | Mechanical Beast | 0.027 | no |
2021 | 331549 | MiniQuest Adventures | 0.027 | no |
2021 | 263222 | Shards of the Jaguar | 0.027 | no |
2023 | 298086 | The Fog: Escape from Paradise | 0.026 | no |
2021 | 282700 | LOOP: Life of Ordinary People | 0.026 | no |
2021 | 348461 | Castle Break | 0.026 | no |
2021 | 327076 | Cartaventura: Lhasa | 0.026 | no |
2021 | 327077 | Cartaventura: Vinland | 0.026 | no |
2022 | 338460 | The Isle of Cats: Explore & Draw | 0.025 | no |
2021 | 265635 | Space Race | 0.025 | no |
2021 | 334644 | Nicodemus | 0.025 | no |
2021 | 334590 | For Northwood! A Solo Trick-Taking Game | 0.025 | no |
2022 | 320718 | Hidden Leaders | 0.025 | no |
2021 | 320960 | Roll In One | 0.025 | no |
2021 | 337765 | Brian Boru: High King of Ireland | 0.024 | no |
2022 | 344839 | Dog Lover | 0.024 | no |
2022 | 308028 | Drop Drive | 0.024 | no |